Lightweight Resource Scaling for Cloud Applications
Elastic resource provisioning is a key feature of cloud computing, allowing users to scale up or down resource allocation for their applications at run-time. To date, most practical approaches to managing elasticity are based on allocation/de-allocation of the virtual machine (VM) instances to the a...
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| Vydané v: | 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing s. 644 - 651 |
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| Hlavní autori: | , , , |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
IEEE
01.05.2012
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| ISBN: | 1467313955, 9781467313957 |
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| Abstract | Elastic resource provisioning is a key feature of cloud computing, allowing users to scale up or down resource allocation for their applications at run-time. To date, most practical approaches to managing elasticity are based on allocation/de-allocation of the virtual machine (VM) instances to the application. This VM-level elasticity typically incurs both considerable overhead and extra costs, especially for applications with rapidly fluctuating demands. In this paper, we propose a lightweight approach to enable cost-effective elasticity for cloud applications. Our approach operates fine-grained scaling at the resource level itself (CPUs, memory, I/O, etc) in addition to VM-level scaling. We also present the design and implementation of an intelligent platform for light-weight resource management of cloud applications. We describe our algorithms for light-weight scaling and VM-level scaling and show their interaction. We then use an industry standard benchmark to evaluate the effectiveness of our approach and compare its performance against traditional approaches. |
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| AbstractList | Elastic resource provisioning is a key feature of cloud computing, allowing users to scale up or down resource allocation for their applications at run-time. To date, most practical approaches to managing elasticity are based on allocation/de-allocation of the virtual machine (VM) instances to the application. This VM-level elasticity typically incurs both considerable overhead and extra costs, especially for applications with rapidly fluctuating demands. In this paper, we propose a lightweight approach to enable cost-effective elasticity for cloud applications. Our approach operates fine-grained scaling at the resource level itself (CPUs, memory, I/O, etc) in addition to VM-level scaling. We also present the design and implementation of an intelligent platform for light-weight resource management of cloud applications. We describe our algorithms for light-weight scaling and VM-level scaling and show their interaction. We then use an industry standard benchmark to evaluate the effectiveness of our approach and compare its performance against traditional approaches. |
| Author | Guo, Li Ghanem, Moustafa M. Han, Rui Guo, Yike |
| Author_xml | – sequence: 1 givenname: Rui surname: Han fullname: Han, Rui email: r.han10@imperial.ac.uk organization: Dept. of Comput., Imperial Coll. London, London, UK – sequence: 2 givenname: Li surname: Guo fullname: Guo, Li email: liguo@imperial.ac.uk organization: Dept. of Comput., Imperial Coll. London, London, UK – sequence: 3 givenname: Moustafa M. surname: Ghanem fullname: Ghanem, Moustafa M. email: mmg@imperial.ac.uk organization: Dept. of Comput., Imperial Coll. London, London, UK – sequence: 4 givenname: Yike surname: Guo fullname: Guo, Yike email: y.guo@imperial.ac.uk organization: Dept. of Comput., Imperial Coll. London, London, UK |
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| SubjectTerms | Cloud computing lightweight scaling Monitoring Quality of service resource allocation algorithms Resource management Servers Time factors |
| Title | Lightweight Resource Scaling for Cloud Applications |
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